The present invention generally relates to packet data communication networks, such as wireless communication networks adapted for packet data services, and particularly relates to improving service scheduling in such networks.
Service scheduling plays an increasingly prevalent role in at least some types of packet data networks. For example, wireless communication networks, such as cellular radio networks, commonly use service schedulers on the forward and/or reverse radio links to control the scheduling of data transmissions to selected users or groups of users. In such scenarios, it is common for a radio base station to maintain data queues for incoming packet data targeted for delivery to individual mobile stations, or groups of mobile stations, whose packet data connections with the radio network are being supported by the radio base station.
A service scheduler within the radio base station transmits data from individual queues according to overall service objectives and according to connection-specific service criteria. That is, given ones of the data connections may have specific Quality-of-Service (QoS) and/or Grade-of-Service (GoS) constraints associated with them that require specific consideration by the service scheduler. For example, certain data connections may have minimum or maximum requirements for data rate, packet latency or overall packet delay, packet jitter, etc., that cannot (or should not) be violated by the service scheduler.
In particular, many types of packet data traffic are delay sensitive and have maximum delay budgets associated with them. Video conferencing and voice applications based on packet data protocols represent two types of delay sensitive applications, each associated with specified maximum delay budgets that stipulate the maximum delivery delay that can be tolerated while still maintaining acceptable application performance. For example, the ITU G.114 for voice delay recommends a maximum end-to-end delay of 280 milliseconds (ms) for satisfactory service.
Constrained delay budgets present service schedulers with significant challenges. For example, maximizing aggregate data throughput and/or maximizing the number of users simultaneously supported represent common goals in wireless communication networks. Thus, air interface service schedulers commonly include scheduling functions that tend to give scheduling preference to users in better radio conditions, as those users can be served at higher data rates. Serving users at higher data rates decreases the amount of time needed, serves them via the oftentimes-limited interface resources, and improves the aggregate data throughput of the scheduler.
However, if some of the packet data to be delivered by the scheduler over the air interface has a maximum delay budget associated with it, the scheduler may be forced to schedule such data for delivery, even if the user(s) targeted to receive the data are not in good radio conditions. More particularly, the conventional scheduler does not know how much of the delay budget has already been consumed by the time it receives a given data packet for transmission, and thus it does not know how much delay budget time remains available for scheduling actual delivery of that packet to the targeted user(s) via transmission over the air interface.